The combination of expanded HIV testing, rapid entry into care and initiation of ART at early stages of disease has been promoted as a method to decrease HIV transmission.(1, 2, 3) The key factor associated with reduced HIV transmission is viral suppression.(4, 5, 6) As such, both early entry and retention in care are important factors in assessing the promise of this strategy. Many studies have examined these factors but no single report offers the definite estimate of the proportion of HIV-diagnosed persons entering care early and staying in care.

Objective

To estimate the proportion of HIV-diagnosed persons who enter care shortly after diagnosis and stay in care.

Search Strategy

PubMed, EMBASE, and CINAHL were searched for reports of published between 1996 and 2009, including those published electronically ahead of print. The search used "HIV" and "care" cross-referenced with terms that indicate medical care and entry and retention in care.

Studies

To be included, studies must have been conducted in the United States, have begun data collection no earlier than May 1995, and have reported data on entry into medical care or retention in care. Surveillance, observational or epidemiologic studies were included. Data from the control arm of intervention studies to improve entry or retention were also included. For the entry into care outcome, studies that reported the proportion of diagnosed persons who entered care in specified time intervals were included. For the retention outcome, studies were included if they included data on multiple visits for HIV care in a specified time interval (e.g. three visits in 12 months). Only studies that enrolled patients who had an initial clinic visit and then followed patients for future visits were included.

Outcome Measures

The proportion of HIV-diagnosed persons who entered care within four months of diagnosis and the proportion of persons who had multiple care visits.

For each study a proportion was calculated by dividing the number of participants with the outcome by the total number of participants in the study. Each proportion was multiplied by its corresponding weight (inverse variance). These were summed across findings and divided by the sum of the weights. Individual proportions were first converted to logits to meet the normal distribution assumption. Final results were presented as proportions. The aggregated findings were based on a random effects model because of significant heterogeneity in the data. A sensitivity analysis was done by comparing the aggregated results with results obtained after iterations using k-1 findings (removing a finding and calculating the aggregated effect size based on the remaining findings). The analysis was also repeated after excluding two studies that each had substantially longer intervals than most. Publication bias was explored through inspection of funnel plots of logit scores and standard errors; bias was not observed.

Conclusions

A total of 3,836 citations were identified and 3,523 of these were excluded because they did not address the outcomes of interest. Of the 313 abstracts that were reviewed in greater detail, 165 were excluded due to lack of relevant data. There were 148 full length articles reviewed as well as 32 additional articles obtained through hand-searches of the reference lists of the 148 full articles reviewed. One hundred thirty articles did not meet the inclusion criteria. Fifty articles contributed data, four of which contributed data on both outcomes. There were 26 studies that contributed 28 independent findings on entry into care and produced a total of 53,323 patients. These data were collected from 1995 to 2009 in a number of regions across the US. Sixty-nine percent (95% CI, 66-71; k=28) of patients entered care. Entry into care at four, six, and 12 months was 72, 72, and 64% respectively. Seventy-six percent of patients who were diagnosed in emergency departments/urgent care clinics entered care compared to 67% of patients who were diagnosed in community settings.

There were 28 studies that included data on retention in care from which there were 75,655 patients. Of these, 24 were unique studies on retention in care. Data were collected from 1996 to 2006 and from a wide geographic distribution of the US. The overall aggregated results found that 59% (95% CI 53-65) had multiple clinic visits, regardless of the time from diagnosis. In the k-1 analysis, the estimates ranged from 57.5% to 60.7%. When the two studies with longer duration were excluded 62% (95% CI 57-66%) of patients had multiple clinic visits. The percentage of patients retained in care was higher in studies conducted before 2003 compared to later studies. The proportion of patients retained in care differed by the length of the observation time; 69% had two or more visits in six months, 54% in 12 months for two or more visits and 59% in 12 months for three or more visits. Studies that had an observation interval of 18-24 months found 61% retention where as studies with an observation interval of 3-5 years had 26% retention.

In the US, entry into and retention in care is moderately high.

Quality Rating

Although not all of the PRISMA criteria(7) were met, because the analysis was not focused on efficacy, all relevant criteria were met.

Programmatic Implications

The "test and treat" model of integrating care and prevention will only be effective at reducing HIV transmission if testing rates are high, entry into care is rapid, adherence to ART is high, and patients remain in care and follow through with regularly scheduled appointments. This meta-analysis examined two of these criteria in the US and found moderate levels of early entry into care and retention in care. How this translates into reductions in HIV transmission however is not known. While this study provides data on these two variables, the first step in this model of prevention is getting all infected persons tested. As such, while the findings from this study are encouraging they are not adequate to judge the impact of the "test and treat" model in the US and do not address this model in resource-constrained areas.